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Program for deinterlacing in video sequences of different formats
Jirků, Pavel ; Kratochvíl, Tomáš (referee) ; Slanina, Martin (advisor)
The aim of this thesis is a study of advanced algorithms for removing interlacing in digital video sequences. The first part of the work is devoted to the theory, basic knowledge and processing characteristics using multimedia data. The second part is devoted to displaying the signal using interlaced and progressive spacing. The following part is focused on methods of conversion between the interlaced line spacing and progressive spacing. The last part deals with implementation of the proposed methods. The algorithm is implemented in C++ language, which provides sufficiently fast processing algorithms. The conclusion of work is focused in testing and verification of the implemented algorithms.
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Gamification of line-follower robot videorecordings
Soboňa, Tomáš ; Honec, Peter (referee) ; Janáková, Ilona (advisor)
This bacheor’s thesis is concerned with the processing of a vehicle’s trajectory following a black line located on an unchanging white background, and subsequently comparing of the quality of each vehicle’s covered distance on this trajectory. The first part of the thesis describes the theory for recognizing the track, individual graphic tags, as well as detection of important points in the picture and their correlation with points in another picture, for which an algorithm SIFT is used. The second part deals with the description of the program, which was created as part of this work, its classes and methods. The program is written in Python, for image processing is used mainly an open source library OpenCV and, to a lesser extent, the NumPy library. Finally, the results are concluded at the end of the thesis.
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Mapping the Motion of People by a Stationary Camera
Bartl, Vojtěch ; Zemčík, Pavel (referee) ; Herout, Adam (advisor)
The aim of this diploma thesis is to obtain information on the motion of people in a scene from the record of the stationary camera. The procedure to detect exceptional events in the scene was designed. Exceptional events can be fast-moving persons, or persons moving in di erent places than everyone else in the scene. To trace the motion of persons, two algorithms were applied and tested - Optical flow and CAMSHIFT. The analysis of the resulting motions is performed by monitoring the progress of motion, and its comparison with the other motions in the scene. The analysis result is represented by detected exceptional motions that can be found in the video. The areas where the motion occurs in the scene, and where the motion is the most common are also described together with the motion direction analysis. The exceptional motion parts extracted from the video represent the main result of the work.
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Visual Home Security System for iOS-Based Mobile Devices
Bajaník, Filip ; Szőke, Igor (referee) ; Herout, Adam (advisor)
The goal of this diploma thesis is to design and implement a mobile application for home security system on the iOS platform. The application introduces a complex solution allowing the transmission of the audio and video streams between the paired mobile devices using WebRTC. The final module represents universal solution for peer-to-peer audio and video communication. The thesis also deals with the field of computer vision, namely efficient motion detection algorithms. The module for motion detection implements ViBe algorithm using Metal. In case that the motion is detected the application notifies a user with a push notification. Synchronization of application data is implemented using Cloudkit and the data persistance using Realm library.
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Time Lapse from Stationary Camera Image
Ficková, Andrea ; Zemčík, Pavel (referee) ; Herout, Adam (advisor)
The goal of this thesis is to design a system which minimizes or even eliminates the restrictions of time-lapse video captured by a stationary camera. I focused on the three of these restrictions, that I had the opportunity to observe: restless objects, abrupt illumination changes, and undesirable objects. The appearance of restrictions spoils the impression of video and causes a distraction for the object of observation. Within this thesis I designed and implemented a system that can process a captured video stored in the computer and capture time-lapse video from a video stream. The goal of the designed system is to apply one of the algorithms to the corresponding restriction. The main result is the production of a time-lapse video, which will be more pleasant for their observers to watch.
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Hiding Moving Objects in Video Sequences
Dostál, Martin ; Zahrádka, Jiří (referee) ; Španěl, Michal (advisor)
Hiding moving objects in video sequences is an interesting topic in computer vision. In this thesis, a real-time single object tracking and removal method is proposed. An input video is assumed to be captured with static video camera. Motion detection is based on a background subtraction using Mixture of Gaussians as the representation of background. The object tracking is realized by a combination of blobs comparison and computation of optical flow using Lucas-Kanade method. Consequent object removal makes use of created background model.
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Motion detection based on an accelerometer measurement
Štancl, František ; Šimek, Milan (referee) ; Pál, Tamás (advisor)
This thesis is devoted to detect motion and it is focused on energy consumption. The introduction involves possible ways for acceleration measuring and discusses The MEMS technology in accelerometers. It also describes components used in a low-power module and some suggestions leading to resolution of this issue. This thesis includes the module design as well, PCB design and software equipment. Finally, it evaluates the results and the solution accuracy.
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Hand Motion Recognition
Blaho, Juraj ; Beran, Vítězslav (referee) ; Hradiš, Michal (advisor)
The aim of this work is to design and implement a novel computer interface based on detection and tracking of a hand in an image from a single camera. The created interface doesn't require any special hardware and it is possible to use it on a common computer with standard web-camera. The implemented interface was used to create an application, which is able to synthesize keyboard and mouse input events and this way it is able to control existing programs without the need to change their source code. Another contribution of this work is a novel method of automatic data acquisition for training of hand detectors. By using this method it is possible to collect thousands of training examples in a few hours.
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Linear drive control based on object motion detection
Novotná, Eliška ; Harabiš, Vratislav (referee) ; Sekora, Jiří (advisor)
The diploma thesis deals with motion detection and linear drive control. The diploma thesis is divided into a theoretical part, where the part of ultrasonic sensors and linear actuators, including the types of individual linear actuators, is mainly described and explained. The practical part presents the solution itself, both in terms of hardware and software. This part therefore contains the system design together with the flowcharts and the simplified 3D design of the structure. At the end of the work is given a sample of the final structure.
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Moving Object Detection in the Environment of Mobile Robot
Dorotovič, Viktor ; Beran, Vítězslav (referee) ; Veľas, Martin (advisor)
This work's aim is movement detection in the environment of a robot, that may move itself. A 2D occupancy grid representation is used, containing only the currently visible environment, without filtering in time. Motion detection is based on a grid-based particle filter introduced by Tanzmeister et al. in Grid-based Mapping and Tracking in Dynamic Environments using a Uniform Evidential Environment Representation. The system was implemented in the Robot Operating System, which allows for re-use of modules which the solution is composed of. The KITTI Visual Odometry dataset was chosen as a source~of LiDAR data for experiments, along with ground-truth pose information. Ground segmentation based on Loopy Belief Propagation was used to filter the point clouds. The implemeted motion detector is able to distiguish between static and dynamic vehicles in this dataset. Further tests in a simulated environment have shown some shortcomings in the detection of large continuous moving objects.
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